Once you have an overarching data model you can begin to look at definitions of the data down to field level enabling you to create a data dictionary or, perhaps more likely, a thesaurus where definitions necessarily vary across different business functions/information systems. This level of information is essential to support an effective data management policy.
Many of the learning providers taking part in the course data programme have developed data and information management strategies and policies as a result of auditing their data and have created data dictionaries. New College Durham terms its data dictionary an ‘information assets register’ and is taking an enterprise architecture (EA) approach keeping its activities tightly aligned by linking this to an information strategy, and an information projects register.
The college senior management team sees effective data management as a response to external financial pressures.
The University of Hertfordshire was prompted to create a data definitions list detailing how they approached each data item within their course data project and how this might vary for different audiences. This was a ‘live’ document that proved to be a useful starting point for resolving issues. The university now has ‘record once, use multiple times’ established as a key part of its ethos although they note the difficulty of implementing such an approach and, in particular, balancing the need for consistency (which might point to central input of data) against the benefits of distributed data input close to the point of origin.
The university is trying to make the most of the correlations that exist between marketing information and that needed for the key information set (KIS) to apply its philosophy.
Other organisations are also recognising the benefits of having a common data language:
"…the process of defining a unified business process, a single data dictionary that can be utilised across the schools for course metadata and across the various systems and various initiatives (eXchanging course related information (XCRI), key information sets (KIS), the higher education academic achievement report (HEAR) etc) has helped evolve a ubiquitous language that all stakeholders can use."
University of Bradford
"Recent changes in the higher education landscape – the KIS, the HEAR and the Quality Assurance Agency (QAA) now looking at the quality of published material – make this understanding [of data] more important than it has ever been."
University of Hertfordshire
"The data definitions that form part of the course data project have encouraged the college into expanding the number of ‘pieces of information’ held against each course or offering."
The University of Exeter had tried to apply consistent data definitions and standards for a number of years and found that the policy was difficult to enforce while the data was stored in a number of different systems so the University now has a single source of course information in its iPAMS system.
We can reuse that…
"From having migrated our course information from several sources into a central database, we would conclude that you should be careful when making assumptions about the data you plan to inherit."
University of Exeter
"For many staff their activity had not changed, but the use of the outputs of their activity had… In the new system, a different set of staff need to understand the implications of their local decisions and data entry practices and their work underpins the subsequent reuse of the data through the end to end processes now in place."
University of Hertfordshire
"The initial plan for developing the course management system was to find common course identifiers used in existing data sources and use these to aggregate course information from the various databases, spreadsheets and documents. It was found during the analysis of course information sources that few common identifiers were present and that aggregating data would be hard and require significant reworking of the information…"
Edge Hill University